{"title":"阿霉素诱导心脏毒性的铁中毒相关生物标志物和潜在药物预测的生物信息学分析。","authors":"Jian Yu, Jiangtao Wang, Xinya Liu, Cancan Wang, Li Wu, Yuanming Zhang","doi":"10.3389/fcvm.2025.1566782","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Doxorubicin-induced cardiotoxicity (DIC) significantly impacts the survival and prognosis of cancer patients. Ferroptosis is involved in the pathogenesis of DIC, but its specific mechanisms remain unclear. This study aims to explore key genes of ferroptosis in DIC and potential therapeutic drugs using various bioinformatics methods.</p><p><strong>Methods: </strong>This study obtained the GSE106297 and GSE157282 datasets from the GEO database, conducted differential gene expression screening and GSEA enrichment analysis using R software. Subsequently obtained ferroptosis-related genes from FerrDb V2, Genecards, Geneontology, and GSEA databases, performed GO and KEGG enrichment analysis after intersecting them with the differentially expressed genes using a Venn diagram. Utilized LASSO regression, SVM-RFE, and RF algorithms to identify key genes, followed by validation using external datasets (GSE232331, GSE230638) and ROC curve plotting to determine the diagnostic value of key genes. Further validation of the expression levels of key genes were conducted through the establishment of a cell damage model. Constructed an mRNA-miRNA-lncRNA network diagram, and performed immune cell composition analysis using CIBERSORT. Finally, predicted potential drugs for key genes using the DSigDB database.</p><p><strong>Results: </strong>We obtained 119 genes after intersecting 1380 Differentially Expressed Genes (DEGs) with Ferroptosis-Related Genes (FRGs). Three key genes (KLHDC3, NDRG1, SPHK1) were identified through further analysis using LASSO, SAM-RFE and RF. The ROC analysis demonstrated that KLHDC3 and NDRG1 have significant diagnostic value, and qRT-PCR verification results also showed statistical significance. We constructed miRNA-lncRNA networks by identifying target miRNAs for KLHDC3 (hsa-miR-24-3p, hsa-miR-486-3p, hsa-miR-214-3p) and NDRG1 (hsa-miR-4510, hsa-miR-182-5p, hsa-miR-96-5p). Immunoinfiltration analysis revealed the relationship between KLHDC3, NDRG1 and immune cells. Anisomycin emerges as a promising small molecule drug for treating DIC, exhibiting good relative binding with KLHDC3 and NDRG1.</p><p><strong>Conclusion: </strong>KLHDC3 and NDRG1 serve as ferroptosis biomarkers implicated in DIC and demonstrate good diagnostic value. In addition, anisomycin may also be a potential drug for treating DIC.</p>","PeriodicalId":12414,"journal":{"name":"Frontiers in Cardiovascular Medicine","volume":"12 ","pages":"1566782"},"PeriodicalIF":2.8000,"publicationDate":"2025-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12058674/pdf/","citationCount":"0","resultStr":"{\"title\":\"Bioinformatics analysis of ferroptosis-related biomarkers and potential drug predictions in doxorubicin-induced cardiotoxicity.\",\"authors\":\"Jian Yu, Jiangtao Wang, Xinya Liu, Cancan Wang, Li Wu, Yuanming Zhang\",\"doi\":\"10.3389/fcvm.2025.1566782\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Doxorubicin-induced cardiotoxicity (DIC) significantly impacts the survival and prognosis of cancer patients. Ferroptosis is involved in the pathogenesis of DIC, but its specific mechanisms remain unclear. This study aims to explore key genes of ferroptosis in DIC and potential therapeutic drugs using various bioinformatics methods.</p><p><strong>Methods: </strong>This study obtained the GSE106297 and GSE157282 datasets from the GEO database, conducted differential gene expression screening and GSEA enrichment analysis using R software. Subsequently obtained ferroptosis-related genes from FerrDb V2, Genecards, Geneontology, and GSEA databases, performed GO and KEGG enrichment analysis after intersecting them with the differentially expressed genes using a Venn diagram. Utilized LASSO regression, SVM-RFE, and RF algorithms to identify key genes, followed by validation using external datasets (GSE232331, GSE230638) and ROC curve plotting to determine the diagnostic value of key genes. Further validation of the expression levels of key genes were conducted through the establishment of a cell damage model. Constructed an mRNA-miRNA-lncRNA network diagram, and performed immune cell composition analysis using CIBERSORT. Finally, predicted potential drugs for key genes using the DSigDB database.</p><p><strong>Results: </strong>We obtained 119 genes after intersecting 1380 Differentially Expressed Genes (DEGs) with Ferroptosis-Related Genes (FRGs). Three key genes (KLHDC3, NDRG1, SPHK1) were identified through further analysis using LASSO, SAM-RFE and RF. The ROC analysis demonstrated that KLHDC3 and NDRG1 have significant diagnostic value, and qRT-PCR verification results also showed statistical significance. We constructed miRNA-lncRNA networks by identifying target miRNAs for KLHDC3 (hsa-miR-24-3p, hsa-miR-486-3p, hsa-miR-214-3p) and NDRG1 (hsa-miR-4510, hsa-miR-182-5p, hsa-miR-96-5p). Immunoinfiltration analysis revealed the relationship between KLHDC3, NDRG1 and immune cells. Anisomycin emerges as a promising small molecule drug for treating DIC, exhibiting good relative binding with KLHDC3 and NDRG1.</p><p><strong>Conclusion: </strong>KLHDC3 and NDRG1 serve as ferroptosis biomarkers implicated in DIC and demonstrate good diagnostic value. In addition, anisomycin may also be a potential drug for treating DIC.</p>\",\"PeriodicalId\":12414,\"journal\":{\"name\":\"Frontiers in Cardiovascular Medicine\",\"volume\":\"12 \",\"pages\":\"1566782\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2025-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12058674/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Frontiers in Cardiovascular Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.3389/fcvm.2025.1566782\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"CARDIAC & CARDIOVASCULAR SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Cardiovascular Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fcvm.2025.1566782","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
Bioinformatics analysis of ferroptosis-related biomarkers and potential drug predictions in doxorubicin-induced cardiotoxicity.
Background: Doxorubicin-induced cardiotoxicity (DIC) significantly impacts the survival and prognosis of cancer patients. Ferroptosis is involved in the pathogenesis of DIC, but its specific mechanisms remain unclear. This study aims to explore key genes of ferroptosis in DIC and potential therapeutic drugs using various bioinformatics methods.
Methods: This study obtained the GSE106297 and GSE157282 datasets from the GEO database, conducted differential gene expression screening and GSEA enrichment analysis using R software. Subsequently obtained ferroptosis-related genes from FerrDb V2, Genecards, Geneontology, and GSEA databases, performed GO and KEGG enrichment analysis after intersecting them with the differentially expressed genes using a Venn diagram. Utilized LASSO regression, SVM-RFE, and RF algorithms to identify key genes, followed by validation using external datasets (GSE232331, GSE230638) and ROC curve plotting to determine the diagnostic value of key genes. Further validation of the expression levels of key genes were conducted through the establishment of a cell damage model. Constructed an mRNA-miRNA-lncRNA network diagram, and performed immune cell composition analysis using CIBERSORT. Finally, predicted potential drugs for key genes using the DSigDB database.
Results: We obtained 119 genes after intersecting 1380 Differentially Expressed Genes (DEGs) with Ferroptosis-Related Genes (FRGs). Three key genes (KLHDC3, NDRG1, SPHK1) were identified through further analysis using LASSO, SAM-RFE and RF. The ROC analysis demonstrated that KLHDC3 and NDRG1 have significant diagnostic value, and qRT-PCR verification results also showed statistical significance. We constructed miRNA-lncRNA networks by identifying target miRNAs for KLHDC3 (hsa-miR-24-3p, hsa-miR-486-3p, hsa-miR-214-3p) and NDRG1 (hsa-miR-4510, hsa-miR-182-5p, hsa-miR-96-5p). Immunoinfiltration analysis revealed the relationship between KLHDC3, NDRG1 and immune cells. Anisomycin emerges as a promising small molecule drug for treating DIC, exhibiting good relative binding with KLHDC3 and NDRG1.
Conclusion: KLHDC3 and NDRG1 serve as ferroptosis biomarkers implicated in DIC and demonstrate good diagnostic value. In addition, anisomycin may also be a potential drug for treating DIC.
期刊介绍:
Frontiers? Which frontiers? Where exactly are the frontiers of cardiovascular medicine? And who should be defining these frontiers?
At Frontiers in Cardiovascular Medicine we believe it is worth being curious to foresee and explore beyond the current frontiers. In other words, we would like, through the articles published by our community journal Frontiers in Cardiovascular Medicine, to anticipate the future of cardiovascular medicine, and thus better prevent cardiovascular disorders and improve therapeutic options and outcomes of our patients.